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The dynamics of resource spending in a competition between political parties: general notes on the Red Queen effect

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  • Alex Coram

    (Robert Gordon University, Scotland, and The University of Western Australia)

Abstract

Competition between political parties is a process that unfolds over time whereas formal theories of party competition have tended to take an essentially static, or one-shot, approach. This leaves some gaps in our understanding of the dynamics of campaigning. The aim of this paper is to make up some of this gap. This is done using a differential game theory model to analyse a situation in which support for a party depends on the amount spent on marketing relative to the expenditure of the other party. One of the main results is that, even when voters are not myopic, the logic of the competition forces parties to accelerate expenditure on campaigning during the period between elections. JEL Categories: C61, C72, C73, D72.

Suggested Citation

  • Alex Coram, 2008. "The dynamics of resource spending in a competition between political parties: general notes on the Red Queen effect," UMASS Amherst Economics Working Papers 2008-01, University of Massachusetts Amherst, Department of Economics.
    • Handle: RePEc:ums:papers:2008-01
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    References listed on IDEAS

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    1. Adams, James, 2001. "A Theory of Spatial Competition with Biased Voters: Party Policies Viewed Temporally and Comparatively," British Journal of Political Science, Cambridge University Press, vol. 31(1), pages 121-158, January.
    2. Jan-Benedict E. M. Steenkamp & Vincent R. Nijs & Dominique M. Hanssens & Marnik G. Dekimpe, 2005. "Competitive Reactions to Advertising and Promotion Attacks," Marketing Science, INFORMS, vol. 24(1), pages 35-54, September.
    3. George Stigler, 1972. "Economic competition and political competition," Public Choice, Springer, vol. 13(1), pages 91-106, September.
    4. Stimson, James A. & Mackuen, Michael B. & Erikson, Robert S., 1995. "Dynamic Representation," American Political Science Review, Cambridge University Press, vol. 89(3), pages 543-565, September.
    5. J. Miguel Villas-Boas, 1993. "Predicting Advertising Pulsing Policies in an Oligopoly: A Model and Empirical Test," Marketing Science, INFORMS, vol. 12(1), pages 88-102.
    6. Pradeep K. Chintagunta & Naufel J. Vilcassim, 1992. "An Empirical Investigation of Advertising Strategies in a Dynamic Duopoly," Management Science, INFORMS, vol. 38(9), pages 1230-1244, September.
    7. Gila E. Fruchter & Shlomo Kalish, 1997. "Closed-Loop Advertising Strategies in a Duopoly," Management Science, INFORMS, vol. 43(1), pages 54-63, January.
    8. Denemark, David, 2002. "Television Effects and Voter Decision Making in Australia: A Re-examination of the Converse Model," British Journal of Political Science, Cambridge University Press, vol. 32(4), pages 663-690, October.
    9. Crain, William Mark & Tollison, Robert D, 1976. "Campaign Expenditures and Political Competition," Journal of Law and Economics, University of Chicago Press, vol. 19(1), pages 177-188, April.
    10. Weingast, Barry R & Shepsle, Kenneth A & Johnsen, Christopher, 1981. "The Political Economy of Benefits and Costs: A Neoclassical Approach to Distributive Politics," Journal of Political Economy, University of Chicago Press, vol. 89(4), pages 642-664, August.
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    More about this item

    Keywords

    party competition; dynamics; differential games.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

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